---
title: 'Senior Site Reliability Engineer - Fleet at Lambda'
canonical: 'https://feeny.ai/job/senior-site-reliability-engineer-fleet-lambda-san-francisco-33fy0znbk8rz'
type: 'job'
last_seen: '2026-09-06'
---

# Senior Site Reliability Engineer - Fleet at Lambda

- **Company:** Lambda
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-01
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/lambda/d4e6f207-73c3-43d1-aa4b-d840ad2254d4

## Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.

*Note: This position requires presence in our San Francisco or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

## What You’ll Do

- Build and operate monitoring and alerting for cluster health — fabric, GPU, power/thermal, and job-level signals — to detect and respond to issues proactively
- Remotely deploy and configure large-scale HPC clusters for AI workloads using automation wherever possible
- Automate cluster lifecycle: operating systems, firmware, drivers, and networking, managed as code (Ansible, Terraform) rather than by hand
- Create runbooks and automated remediations for common cluster failure modes, designed so Support and HPC Support can run them safely
- Troubleshoot and resolve cluster issues across InfiniBand/RoCE, NCCL, GPU-direct, fabric, switching, and power — working closely with on-site deployment teams
- Participate in on-call rotations and lead incident response for cluster-level problems
- Contribute to and maintain Standard Operating Procedures, and feed clear requirements back to other engineering teams on simplification, stability, and operational efficiency

You

- 7+ years of experience in Site Reliability Engineering, HPC Engineering, DevOps, or a similar role
- Have a strong understanding of modern AI infrastructure, from GPU architectures to hardware performance optimization
- Strong understanding of Linux-based systems in a distributed environment
- Are experienced configuring and troubleshooting InfiniBand (IB), RoCE, CLOS fabrics, 100GbE, Ethernet/switching, GPU-direct, and NCCL environments
- Solid understanding of Python and Go, with experience working with SWE teams to improve internal tooling.
- Experience with monitoring and alerting tools (e.g., Prometheus, Grafana, Clickhouse)
- Proficiency in automation and configuration management tools (e.g., Ansible, Terraform)
- Have excellent problem-solving and troubleshooting skills and an innate attention to detail
- Passion for continuous improvement and innovation

## Nice to Have

- Experience with machine learning / deep learning frameworks (PyTorch, TensorFlow) and benchmarking tools (DeepSpeed, MLPerf)
- Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes)
- Experience building and/or operating HPC resources.
- Depth in the NVIDIA hardware and firmware ecosystem
- Experience with data center power and thermal design
- Background in chaos engineering or similar reliability testing methodologies
- Understanding of compliance frameworks (SOC 2, ISO 27001, etc.)

Salary Range Information

The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

## About Lambda

- Founded in 2012, with 500+ employees, and growing fast
- Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
- We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- Our values are publicly available: https://lambda.ai/careers
- We offer generous cash & equity compensation
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use

## Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

## About Lambda

## Company Overview
- **One-liner**: Lambda builds supercomputers and cloud infrastructure for training and deploying large-scale AI models, from single GPUs to gigawatt-scale AI factories.
- **Entity Type**: Private (funding stage not publicly disclosed; founded by ML engineers)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2012
- **Founders**: Stephen Balaban and Michael Balaban

## Core Business
- Primary industry: AI infrastructure / cloud computing for machine learning.
- Target customers: Frontier AI labs building large foundation models, hyperscalers scaling global AI infrastructure, and enterprises deploying AI in regulated industries (B2B, Enterprise).
- Mission: “Make compute as ubiquitous as electricity and give everyone in America the power of superintelligence” (also “One person, one GPU”).

## Products & Services
- **The Superintelligence Cloud**: A suite of cloud computing offerings specifically built for AI workloads, including:
  - **GPU Instances**: On-demand NVIDIA HGX B200, H100, and GB300 NVL72 instances for prototyping and testing.
  - **Managed Clusters**: Dedicated, single-tenant clusters (e.g., NVIDIA GB300 NVL72, HGX B200/H100) with full management and co-engineering from Lambda’s team.
  - **1-Click Clusters™**: Rapidly deployable clusters for training and inference.
  - **Superclusters**: Large-scale AI factories integrating high-density power, liquid cooling, and high-bandwidth interconnects.
- **AI Infrastructure Hardware**: Modular AI factory designs and NVIDIA-based systems for on-premise or colocation deployment.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total funding not publicly available; revenue not disclosed.
- **Notable Customers/Partners**: “World’s most advanced AI organizations” (frontier labs, hyperscalers, regulated enterprises). Leadership includes former executives from cloud and networking companies.
- **Growth Signals**: Active hiring across engineering, storage, security, and procurement roles; building AI factories at gigawatt scale; SOC 2 Type II certified; expanding from San Francisco to San Jose, CA.

## Competitive Advantages
- **AI‑First DNA**: 100% of engineering, operations, and support dedicated to AI – founded by ML engineers in 2012.
- **Single‑Tenant Isolation**: Shared‑nothing architecture for security and performance, with hardware‑level isolation.
- **Full‑Stack Expertise**: Co‑engineering from the same team building the infrastructure, enabling deep optimization for large training runs.
- **Hacker Culture**: Rooted in the Noisebridge hackerspace values of do‑ocracy, low ego, and “be excellent to each other.”
- **Performance**: Rack‑scale NVIDIA systems (GB300, B200, H100) with high‑speed interconnects (NVIDIA Quantum‑2 InfiniBand).

## Strategic Focus
- Scaling infrastructure to support the next generation of superintelligence, including gigawatt‑scale AI factories.
- Enabling frontier labs to train trillion‑parameter models and serve billions of tokens in production.
- Expanding compliance and security capabilities for regulated industries.
- Growing the cloud platform (The Superintelligence Cloud) as the primary go‑to‑market offering.

## Why Work Here
- **Culture**: Hacker ethos (Noisebridge roots), low ego, no yelling, no politics, no crypto. Values: build, move fast, care, be excellent to each other.
- **Work Environment**: Fast‑paced, high‑change, outcome‑focused. Emphasis on technical excellence and curiosity. Anonymous feedback encouraged.
- **Interview Process**: Clear, structured steps (recruiter chat → hiring manager → technical assessment → panel interviews → reference/offer). Pedigree is not everything; focus on what you’ve built.
- **Location & Remote**: Offices in San Francisco and San Jose, CA. FAQ page addresses remote/hybrid policy (details not provided in available snippets); some roles appear on‑site.
- **Perks**: Benefits, time off, and other perks are listed on the careers site (specifics not extracted here).

## Sources
1. [lambda.ai/about](https://lambda.ai/about)
2. [lambda.ai/](https://lambda.ai/)
3. [lambda.ai/careers](https://lambda.ai/careers)
4. [lambda.ai/leadership](https://lambda.ai/leadership)

## Other roles at Lambda

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- [Senior Manager, Detection and Response](https://feeny.ai/job/senior-manager-detection-and-response-lambda-bellevue-f6jvw1b07xwk) — Bellevue, WA
- [Data Center Construction Site Foreman (Dallas)](https://feeny.ai/job/data-center-construction-site-foreman-dallas-lambda-united-states-vc7fg15nb275) — United States
- [Construction Administrator](https://feeny.ai/job/construction-administrator-lambda-san-jose-ky6swv0mtr9v) — San Jose, CA
- [Commodity Sourcing Manager – AI Infrastructure](https://feeny.ai/job/commodity-sourcing-manager-ai-infrastructure-lambda-san-jose-9zfy7qfg5bw5) — San Jose, CA
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